<p></p>
<div class="container">
<div class="row text-center">
<div class="col-xs-12">
<h2>[Insert Title]</h2>
<p>[Insert Text]</p>
</div>
</div>
</div>
<p></p>
<p></p>
<div class="diag-divider gray-line-rl"> </div>
<p></p>
<p></p>
<div class="container">
<div class="row fifty-fifty media-first">
<div class="col-xs-12 col-sm-6 vcenter">
<h2>[Insert Title]</h2>
<p>[Insert Text]</p>
</div>
<div class="col-xs-12 col-sm-6 vcenter media">[Insert Image]</div>
</div>
</div>
<p></p>

Putting Data Discoveries to Use at theScore


<p><a href="https://www.thescore.com/" target="_blank" rel="noreferrer noopener" aria-label="theScore (opens in a new tab)">theScore</a> is one of the most popular sports apps in North America, with millions of users using it to get real-time stats, scores, and breaking news alerts from their favorite teams in 40+ leagues.</p>


<p>theScore needed to share data more easily across the company, even with non-technical users. Sisense&#8217;s self-service capabilities have empowered everyone to dive deeper into their data.</p>


<p>&#8220;In this day and age, data is paramount. When you&#8217;re building consumer experiences, you need to look at the data to understand and figure out what&#8217;s next,&#8221; said Riaz Lalani, VP of Product at theScore. &#8220;We mostly use Sisense to ask specific questions so we can tell stories with data.&#8221; </p>


<p>&#8220;We were looking for a self-service solution for quite a while,&#8221; said Andrew Konrad, Director of Analytics &amp; AdTech at theScore. &#8220;We wanted people to be able to access their data more easily, including those who weren&#8217;t incredibly technical but want to dive a bit deeper than a regular dashboard.&#8221; </p>


<p>Konrad says that by opening up the rest of his team to explore data on their own, it frees him and the rest of the analytics team up to do more complex analysis or build machine learning models, rather than just creating dashboards for the rest of his team.</p>


<p>&#8220;Being able to do some quick analysis on my own, it really enables us to not bog down the data team with more trivial tasks that I can quickly answer myself,&#8221; said Samuel Kim, Product Manager, Growth at theScore. &#8220;We have huge competitors in the sports app world, so we need to make those decisions fast. Sisense really arms us with the information we need to act quickly.&#8221; </p>


<p>Lalani says that Sisense&#8217;s ease of use and strong self-service capabilities allow the whole team at theScore to answer questions more quickly, making them more agile and ensuring they deliver more value to their users at the fastest pace possible.</p>


<p>&#8220;Ultimately, that creates business value because our customers will be more engaged and love our product even more,&#8221; said Lalani. &#8220;We really need to understand our business more in order to make the right decisions, and Sisense helps us identify those things really quickly.&#8221; </p>


<p>Konrad says his team had looked at other analytics systems before but found it&#8217;d take a while to set up and was far too expensive. That wouldn&#8217;t work for theScore, a fast-moving company that was impatient and wanted to get answers quickly.</p>


<p>&#8220;We run a hypothesis-driven product culture here – what that means is we think very deeply about what the customer wants, and develop a strong hypothesis around it,&#8221; said Riaz Lalani, VP of Product at theScore. &#8220;We mostly use Sisense to ask specific questions, to help model out specific outcomes. By doing so, we can easily validate whether we&#8217;re going down the right path with any new innovation or feature we deliver.&#8221; </p>


<p>In only nine months, Sisense has helped theScore developed a much greater focus on experimentation, said Kim. &#8220;Our whole team is digging deeper into their data to draw out insights about where they can improve and grow,&#8221; said Kim. &#8220;The data has always existed, but now there&#8217;s this company commitment to using it to really drive insights and acting against it.&#8221;</p>


<p>Konrad&#8217;s analytics team has also taken the analysis one step further – they built a machine-learning algorithm to predict how their campaigns will do. They fed all of the data from that algorithm through Sisense so the team would have nice charts to understand how many users they&#8217;d expect from each campaign and how much it would cost them.</p>


<p>&#8220;To do that, we would take all this data from all these different places, we&#8217;d give them a score and an LTV so they can make very quick decisions on it,&#8221; said Konrad. &#8220;And the only place to put all of this, and have it feed into this one place where everybody can look at it, was Sisense.&#8221;</p>


<p>&#8220;Just knowing that we have that data accessible every single day, that&#8217;s going to help the company grow,&#8221; said Darren Kritzer, Managing Editor at theScore. &#8220;It will help content grow and get better. For anything you are curious about, Sisense is there to help.&#8221;</p>
